1. Field of the Invention
The present invention relates to a myoelectric-pattern classification method and apparatus in a method of interfacing muscle action potential (myoelectric pattern).
2. Description of the Prior Art
FIG. 2 is a drawing used to illustrate a prior-art apparatus that manipulates a target by extracting a feature value from a myoelectric pattern, encoding it into a bit string and classifying the encoded bit pattern. In the drawing, {circle around (1)} denotes myoelectric patterns, {circle around (2)} a surface electrode group, {circle around (3)} amplification and smoothing apparatuses, {circle around (4)} a feature-pattern extraction apparatus, {circle around (5)} an encoder (binary code/gray code), {circle around (6)} a pattern classifier, and {circle around (7)} a control target such as a motor, a robot, a device for the disabled, rehabilitation device, a myoelectric arm prosthesis, a game, and so forth.
As shown in the drawing, a myoelectric pattern {circle around (1)} that is an action potential generated by the coordinated action of a plurality of muscles, is measured by one or a plurality of surface electrode groups {circle around (2)} on a skin surface. What is measured is the sum of the action potentials generated by the plurality of muscles. Next, the sum potential obtained is subjected to amplification and smoothing by the amplification and smoothing apparatuses {circle around (3)}. The feature-pattern extraction apparatus {circle around (4)} extracts a feature pattern from the amplified, smoothed signal. The encoder {circle around (5)} encodes the obtained feature pattern into a binary-code or gray-code bit-string. The pattern classifier {circle around (6)} classifies the encoded patterns and generates signals to control the control target {circle around (7)}.
Because such conventional technlogy uses binary codes or gray codes, such as shown in Table 1, for the encoding, in which it takes time to design the pattern there are cases in which complex pattern classifiers are required. This has been a problem standing in the way of reducing the size and cost, preventing the apparatus coming into widespread use as a myoelectric pattern interface.
TABLE 1Gray codeBinary codeFeature valueX1X2X3X4X1X2X3X4 000000000 100010001 200110010 300100011 401100100 501110101 601010110 701000111 811001000 911011001101111101011111010111210101100131011110114100111101510001111
In the case of binary code and gray code, involuntary changes in myoelectric patterns caused by changes in muscle tone can make it difficult to achieve correct pattern classification; accordingly, the range of applicability has been limited.
An object of the present invention is to resolve the above problems by providing a compact, low-price myoelectric-pattern classification method and apparatus that can be achieved by means of a simple processor and table-lookup apparatus.
Another object of the present invention is to provide a myoelectric-pattern classification method and apparatus that improve classification accuracy and promote the wider use of a myoelectric interface method and apparatus.